The goal of observational study is to evaluate effectiveness of predicting the integrity of interlobar fissures based on chest image AI technology in patients with Chronic Obstructive Pulmonary Disease who will undergo lung volume reduction surgery with endobronchial valve implantation. The main question it aims to answer is: evaluation of the effectiveness of predicting the integrity of interlobar fissures based on chest image AI technology.

Participants will be evaluated by lung CT (quantitative analysis based on chest image AI technology and artificial analysis) and imported Chartis detection system.

Inclusion Criteria:

• Patients with chronic obstructive pulmonary disease who meet the GOLD diagnostic criteria
• FEV1 ≤ 45% pred and FEV1/FVC<70%
• TLC>100% pred and RV>175% pred
• CAT≥18
• >50% of emphysema destruction
• Smoking prohibition>6 months
• Sign the informed consent form

Exclusion Criteria:

• PaCO2>8.0 kPa, or PaO2<6.0 kPa
• 6-minute walking test<160m
• Obvious chronic bronchitis, bronchiectasis or other infectious lung diseases
• Three hospitalizations due to pulmonary infection in the past 12 months before the baseline assessment
• Previous lobectomy, LVRS or lung transplantation
• LVEF<45% and or RVSP>50mmHg
• Anticoagulant therapy that cannot be stopped before surgery
• The patient has obvious immune deficiency
• Participated in other lung drug studies within 30 days before this study
• Pulmonary nodules requiring intervention
• Any disease or condition that interferes with the completion of the initial or subsequent assessment

chronic obstructive pulmonary diseases